The present invention relates to the development of an automatic zone monitoring system for use in the identification of zone infringements in applications such as security, health and safety, working practices analysis and traffic analysis.
The use of video cameras in monitoring behaviour is increasing. In particular video cameras are now routinely used for security purposes and, whilst the majority of these systems are monitored manually, a number of systems have been developed to automatically analyze the resultant video feed. Much work has been done by the Universities of Leeds and Reading in the United Kingdom on the recognition and extraction of objects in video. The University of Leeds has developed algorithms to detect deformable objects, such as humans, using Hidden Markov Model techniques to help in the identification of pixel clusters as humans, and to predict their behaviour when information loss occurs, e.g. due to occlusion by foreground objects. The University of Reading has done research in the area of identifying rigid structures in video, such as vehicles, in a similar way.
In any case, both establishments have demonstrated the ability to identify objects by colour coding a bounding box around each object. See, for example, http://www.scs.leeds.ac.uk/imv/index.html.
Typically these security-systems involve static cameras monitoring regions in the view of a single camera. For example, anyone approaching a safe in a bank might trigger an alarm. These systems have no inherent understanding of the 3-D nature of the real world, so they cannot distinguish between a small object close to the camera and a large object far away. This is not a problem with applications which closely-monitor high-value/danger items which are not moving around.
In dynamic situations such as may be found in building sites for example, a single wide-angle camera may be covering a large zone, and 2-D aware systems may well trigger false alarms when, for eg, a crane lifts a load into the air, and visually the load (which may be close to the camera, and perfectly safe) might line-up with a more-distant object being monitored.
Surveillance systems which rely on manual analysis face a further problem in that they do not support the determination of more routine behavioral patterns and do not facilitate changes in the state of prohibited areas.
For example, in a health and safety application there may be regular occurrences of an employee passing through a danger area due to poor site design. Alternatively, the volume of the prohibited region may vary according to the state of dangerous equipment.
The present invention provides an automatic zone monitoring system comprising: means for capturing live video using a plurality of video cameras; and processing means connected to said video cameras comprising: means for automatically identifying moving objects within the field of view of said video cameras; means for defining one or more 3 dimensional monitored volumes; and means for detecting the intersection between said moving objects and the or each monitored volume.